Design for Six Sigma Statistics, Chapter 3 - Describing Random Behavior
Here is a chapter from Design for Six Sigma Statistics, written by a Six Sigma practitioner with more than two decades of DFSS experience who provides a detailed, goal-focused roadmap. It shows you how to execute advanced mathematical procedures specifically aimed at implementing, fine-tuning, or maximizing DFSS projects to yield optimal results. For virtually every instance and situation, you are shown how to select and use appropriate mathematical methods to meet the challenges of today's engineering design for quality.
What people are saying - Write a review
We haven't found any reviews in the usual places.
16 modules 24 hours Bernoulli trials binomial distribution binomial random variable Calculating Probability center of gravity clutch continuous medium continuous random variable defective disks defective items defined denoted DFSS discrete random variable engineering equally likely outcomes Eric exactly x defective Example expected number expected value families of random Figure finite population flips three coins fX(x fX(x)dx FX[x gears graph heads facing integer Kurt[X kurtosis measure of variation median model is known mutually exclusive events nondefective items normal random variable normally distributed NORMDIST function number of heads number of sixes odd number Oscillator Frequency P[BZA parameters parametric family permutations Platykurtic prediction intervals prob probability model probability of selecting processors properties Quantiles random variable representing real numbers representing the number sample space sampling problems sampling without replacement SD[X shim Six Sigma Skew[X skewed Solution standard deviation standard normal tails Three-Coin Experiment uniformly distributed variance Venn Diagram zero